Extreme value models and techniques are widely applied in environmental studies to define protection systems against the effects of extreme levels of environmental processes. Regarding the matter related to the climate change science, a certain importance is cover by the implication of changes in the hydrological cycle. Among all hydrologic processes, rainfall is a very important variable as it is a fundamental component of flood risk mitigation and drought assessment, as well as water resources availability and management. We implement a geoadditive mixed model for extremes with a temporal random effect assuming that the observations follow generalized extreme value distribution with spatially dependent location. The analyzed territory is the catchment area of Arno River in Tuscany in Central Italy.

This work has the purpose of inquiring into the presence of an urban hierarchy within second-tier city areas and alternative agglomeration models differing in their self-propelling ability and territorial sustainability. To this aim we confront regional polycentric areas, by going inside the traditional agglomeration and variety economies and the land settlement model of small-medium urban poles. In particular, the present work compares four Italian regions characterized by a territorial development driven by second-tier cities. The first two sections of the paper evaluate the functional pattern of the different urban systems and subsequently measure their rank in terms of extra-regional attractiveness on demand, which is expressed by rare services (Sections 2 and 3). Sections 4 and 5 tackle the issue of sustainability of settlements by taking into account land consumption and the degree of territorial fragmentation caused by different urbanization models. We discovered good urban performances and settlement sustainability of the second-tier cities agglomeration model in Italian regions, which is stronger when based on the co-presence of specialized small cities (which can assure a minimum amount of local demand for advanced services) and a multifunctional medium urban centre (which can ensure rarer functions). These findings bring strong recommendations on urban policies.

This paper aims to estimate, through the use of a spatial model, the determinants of fiscal policies on property tax adopted by Italian municipalities in 2014, to assess the existence of strategic interactions influencing their revenue decisions and, finally, to investigate the possible sources of such tax mimicking. The analysis evaluates the impact of political and socio-economic variables on the local policy decisions and confirms that the choices on property tax are influenced by the neighbouring municipalities' behaviour.With regard to the tax mimicking sources, results highlight that the imitative behaviour among municipalities on their tax policy is determined mainly from spillover effects, with a decreasing effect in relation to municipal size.

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The mean of a balanced ranked set sample is more efficient than the mean of a simple random sample of equal size and the precision of ranked set sampling may be increased by using an unbalanced allocation when the population distribution is highly skewed. The aim of this paper is to show the practical benefits of the unequal allocation in estimating simultaneously the means of more skewed variables through real data. In particular, the allocation rule suggested in the literature for a single skewed distribution may be easily applied when more than one skewed variable are of interest and an auxiliary variable correlated with them is available. This method can lead to substantial gains in precision for all the study variables with respect to the simple random sampling, and to the balanced ranked set sampling too.