Correction to: Multinational corporations and tax havens: evidence from country‑by‑country reporting

International Tax and Public Finance - The original version of this article contained a mistake in the co-author name “Javier Garcia?Bernando”.     

Prevalence and Forms of Workplace Bullying Among University Employees

Over the past decade, a growing number of Anglo-American and Scandinavian researchers have documented the extent to which the university environment provides opportunities for workplace bullying. By contrast, there has been a visible lack of similar studies in non-Western national contexts, such as the Czech Republic and other Central Eastern European (CEE) countries. The present article addresses this gap by reporting the findings of the first large-scale study into workplace bullying among university employees in the Czech Republic. The exposure to bullying was assessed with the Negative Acts Questionnaire-Revised (NAQ-R) in a sample of 1,533 university employees. The results showed that 13.6 % of the respondents were classified as bullying targets based on an operational definition of bullying (weekly exposure to one negative act), while 7.9 % of the respondents were identified as targets based on self-reports. This prevalence is comparable to bullying rates in Scandinavia but considerably lower than in Anglo-American universities. Differences between Anglo-American and Czech universities were also found with respect to the status of perpetrators (bullying was perpetrated mostly by individual supervisors in the Czech sample), perceived causes of bullying (structural causes perceived as relatively unimportant in the Czech sample), and targets’ responses to bullying (minimal use of formal responses in the Czech sample). The authors propose that cross-cultural differences as well as differences between the Anglo-American model of “neoliberal university” and the Czech model of university governance based on “academic oligarchy” can be used to explain these different findings.     

Assessing the effect of alternative land uses in the provision of water resources: Evidence and policy implications from southern Europe

Ecosystem goods and services have been brought to the forefront of policy making all over the world. It is acknowledged that these goods and services underpin human well-being. The provision of water resources is amongst those services that have raised more attention, given its unquestionable value and global threats like climatic change. Nevertheless, the biophysical basis that determines the land-use/water interactions has been often ignored. For the formulation of sound decisions, it is necessary to extend the empirical basis that determines these complex relations. With this aim, the present paper analyses the effect of alternative types of land cover in the provision of water resources. In doing so, we compare hydrological, meteorological and land-cover data obtained in 15 watersheds located in the Basque Country (Northern Spain). Moreover we discuss the implications of including water resources in land-use policy and planning and address areas for further research.     

Agriculture and climate change in global scenarios: why don't the models agree

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.     

Integrated Management of Land Use Systems under Systemic Risks and Security Targets: A Stochastic Global Biosphere Management Model

Interdependencies among land use systems resemble a complex network connected through demand–supply relationships. Disruption of this network may catalyse systemic risks affecting food, energy, water and environmental security (FEWES) worldwide. We describe the conceptual development, expansion and practical application of a stochastic version of the Global Biosphere Management Model (GLOBIOM), used to assess competition for land use between agriculture, bioenergy and forestry at regional and global scales. In the stochastic version of the model, systemic risks of various kinds are explicitly covered and can be analysed and mitigated in all their interactions. While traditional deterministic scenario analysis produces sets of scenario‐dependent outcomes, stochastic GLOBIOM explicitly derives robust outcomes that leave the systems better‐off, independently of which scenario applies. Stochastic GLOBIOM is formulated as a stochastic optimisation model that is critical for evaluating portfolios of robust interdependent decisions: ex‐ante strategic decisions (production allocation, storage capacities) and ex‐post adaptive (demand, trading, storage control) decisions. As an example, the model is applied to the question of optimal storage facilities, as buffers for production shortfalls, to meet regional and global FEWES requirements when extreme events occur. Expected shortfalls and storage capacities have a close relationship with Value‐at‐Risk (VaR) and Conditional Value‐at‐Risk (CVaR) risk measures. A Value of Stochastic Solutions is calculated to illustrate the benefits of the stochastic over the deterministic model approach.     

Farming system modelling for agri-environmental policy design: The case of a spatially non-aggregated allocation of conservation measures

This paper addresses the issue of designing policies for habitat conservation on agricultural land. The case under study requires a non-aggregated spatial distribution of the fields to be enrolled in an agri-environmental programme. A spatially explicit mathematical programming farm-based model, which accounts for three spatial levels (field, farm and landscape), is coupled with a relevant spatial pattern index (the Ripley L-function) to analyse the design and implementation of an agri-environmental programme aimed to preserve the Tetrax tetrax in the Plaine de Niort, France. The model is run using a stylised map with heterogeneous soil types and both crop growing and mixed dairy farms. Results show that valuable insights into agri-environmental programme design are gained through a detailed representation of farming system management. The suitable, non-aggregated spatial pattern for T. tetrax conservation is more costly than less-suitable, more aggregated patterns, because it tends to require equal participation of all farms. The policy simulations reveal that the various spatial patterns can be obtained through relatively simple uniform contract structures. An effective contract structure entails a set of two degressive payments which encourages all farms to enrol at least a small share of their land in the program.