Finite population properties of predictors based on spatial patterns

When statistical inference is used for spatial prediction, the model-based framework known as kriging is commonly used. The predictor for an unsampled element of a population is a weighted combination of sampled values, in which weights are obtained by estimating the spatial covariance function. This solution can be affected by model misspecification and can be influenced by sampling design properties. In classical design-based finite population inference, these problems can be overcome; nevertheless, spatial solutions are still seldom used for this purpose. Through the efficient use of spatial information, a conceptual framework for design-based estimation has been developed in this study. We propose a standardized weighted predictor for unsampled spatial data, using the population information regarding spatial locations directly in the weighting system. Our procedure does not require model estimation of the spatial pattern because the spatial relationship is captured exclusively based on the Euclidean distances between locations (which are fixed and do not require assessment after sample selection). The individual predictor is a design-based ratio estimator, and we illustrate its properties for simple random sampling.spatial sampling; ratio estimator; design-based inference; model-based inference; spatial information in finite population inference campionamento spaziale, stimatore del rapporto, inferenza da disegno, inferenza da modello; informazione spaziale nell’inferenza da popolazioni finite

A spatial approach to EU regional economic convergence: a comparison between parametric and non-parametric analysis.

The economic convergence among European regions over the period 1980-2006 is analysed in the first place by using a conditional β-convergence model and a distance-based weight matrix and secondarily by a spatially-conditioned stochastic kernel approach. A Spatial Autoregressive model which identifies two spatial regimes and spatial dependence finds that the convergence process is affected by polarization into two clusters defined both on a geographical and economic criterion, which converge at different rates towards different steady states. A similar result is then reached through a non-parametric analysis of the income distribution dynamics. These results confirm the hypothesis that a methodology which uses spatial econometric techniques is needed. They also suggest some implications for EU Regional Policy that should be taken into account.

Measuring the impact of the Italian CFL programme on the job opportunities for the youths

The CFL programme has been introduced in 1985 to improve the youths occupational chances. It provides the employers some incentive to recruit young workers by reducing both the labour and the firing costs relative to those they would bear by recruiting older workers. Following the literature, the expected impact of the programme is to increase the eligibles chance to work during the eligibility period as well as to improve their chance to work after the eligibility period thanks to the longer work experience obtained during the eligibility period. A substitution effect might emerge since as subjects get out of eligibility employers might find convenient to replace them by younger still eligible workers. To measure the impact of the programme we exploit the variation over time and across geographical areas of the incentive to hire eligible workers induced by several reforms of the programme as well as its interaction with other incentive schemes.targeted wage subsidy, firing costs, substitution effect

The Institute for Religious Works: key features of financial intermediation

Corresponding author: F. Arnaboldi, email: [email protected]. While the paper is the result of intense collaboration between the two authors, sections 3 is attributable to F. Arnaboldi and section 1 and 2 to B. Rossignoli. Section 4 is a joint effort. The authors wish to thank P. Mottura and two anonymous referees for their valuable comments. All errors are ours.  Article peer reviewed.SUMMARY: 1. Introduction – 2. Background to anti-money laundering – 3. Financial intermediation, 2011–2014 – 4. Conclusion

The role of knowledge networks in facilitating the creation of climate information services

nowledge networks are collections of individuals and teams who work together across organizational, spatial and disciplinary boundaries to invent and share a body of knowledge. Climate services are tools and application that support decision-making by transforming raw climate data into tailored information. They call for co-development practices in place and for successful collaboration between different stakeholders. Knowledge networks for climate services are intermediaries that facilitate the interaction between upstream (providers) and downstream (user) actors operating at various scales (local, national, regional and supranational). They assist the decision-making process of a wide set of users by creating windows of opportunity and by delivering usable climate information. The aim of this work is to frame and assess the efficiency of knowledge networks for climate services in promoting innovation and facilitate its diffusion. First, we characterize knowledge networks learning from insights of a multidisciplinary literature. Second, we analyse the purpose, the process and the audience of each knowledge network for climate services by screening their programmatic documents. We then assess the efficiency of knowledge networks by performing content analysis of interviews with knowledge network managers and by checking for the existence of inconsistencies or gaps with the initial objectives. We find knowledge networks for climate services pursue four objectives: coordination, innovation promotion, science-policy interface and support to members. We also find inadequate tools to monitor the members activities, but a strong positioning within the climate services domain. On the communication side, knowledge networks for climate services mostly interact with developers of climate services but they face challenges in sharing the members’ activities with users. Our work fills a significant knowledge gap and helps providing new tools of performance assessment in absence of a clearly defined methodology. The identification of bottlenecks and under-performing mechanisms in the climate information services sphere allows the elaboration of strategies to improve the status quo and facilitates the diffusion of these innovations

Mucosa-Environment Interactions in the Pathogenesis of Rheumatoid Arthritis

Mucosal surfaces play a central role in the pathogenesis of rheumatoid arthritis (RA). Several risk factors, such as cigarette smoking, environmental pollution, and periodontitis interact with the host at the mucosal level, triggering immune system activation. Moreover, the alteration of microbiota homeostasis is gaining increased attention for its involvement in the disease pathogenesis, modulating the immune cell response at a local and subsequently at a systemic level. Currently, the onset of the clinical manifest arthritis is thought to be the last step of a series of pathogenic events lasting years. The positivity for anti-citrullinated protein antibodies (ACPAs) and rheumatoid factor (RF), in absence of symptoms, characterizes a preclinical phase of RA namely systemic autoimmune phase- which is at high risk for disease progression. Several immune abnormalities, such as local ACPA production, increased T cell polarization towards a pro-inflammatory phenotype, and innate immune cell activation can be documented in at-risk subjects. Many of these abnormalities are direct consequences of the interaction between the environment and the host, which takes place at the mucosal level. The purpose of this review is to describe the humoral and cellular immune abnormalities detected in subjects at risk of RA, highlighting their origin from the mucosa environment interaction

Finite population properties of predictors based on spatial patterns

When statistical inference is used for spatial prediction, the model-based framework known as kriging is commonly used. The predictor for an unsampled element of a population is a weighted combination of sampled values, in which weights are obtained by estimating the spatial covariance function. This solution can be affected by model misspecification and can be influenced by sampling design properties. In classical design-based finite population inference, these problems can be overcome; nevertheless, spatial solutions are still seldom used for this purpose. Through the efficient use of spatial information, a conceptual framework for design-based estimation has been developed in this study. We propose a standardized weighted predictor for unsampled spatial data, using the population information regarding spatial locations directly in the weighting system. Our procedure does not require model estimation of the spatial pattern because the spatial relationship is captured exclusively based on the Euclidean distances between locations (which are fixed and do not require assessment after sample selection). The individual predictor is a design-based ratio estimator, and we illustrate its properties for simple random sampling

Liquid chromatography tandem mass spectrometry analysis of synthetic coccidiostats in eggs

Coccidiostats are synthetic drugs administered to animals, especially to poultry, to cure coccidiosis. In this paper, we present a selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to analyze residues of five synthetic coccidiostats in eggs: clazuril, diclazuril, robenidine, nicarbazin, toltrazuril and its two metabolites. The extraction efficiency was evaluated by testing several solvents, pH, different volumes and time of extraction. The clean-up procedures were optimized using different solid phase extraction cartridges and different eluants. The chromatographic separation was achieved in reversed phase using a gradient of 0.1% formic acid in water and acetonitrile, whereas the MS detection was performed in negative electrospray ionization (ESI) for all the analytes, except for the robenidine. The developed method has been validated according to Commission Decision 2002/657/CE. The validation parameters, as linearity, precision, recovery, specificity, decision limit (CC alpha), detection capability (CC beta), and robustness have been determined. The proposed method resulted simple, fast, and suitable for screening and confirmation purposes