A fuzzy logic approach to poverty analysis based on the Gini and Bonferroni inequality indices

In the poverty analysis framework, a great deal of attention has been paid to the poverty measurement in terms of monetary variables, such as income or consumption. In this context, a relevant open problem is connected with the distinction between poor and non-poor. In fact, the concept of poverty is rather vague and cannot be defined in a clear way. In this respect, following a fuzzy logic approach, some new poverty measures are proposed. In particular, the fuzzy extension of two existing poverty measures based on the Gini and Bonferroni inequality indices is provided. Some synthetic and real applications are given in order to show how the proposed poverty measures work.     

Simultaneous confidence intervals on partial means of classes in the two-stage stratified sampling

Let’s consider a finite population of P units, each of them assumes a specific amount of the quantitative variable X. Moreover we assume that the range of values of X is subdivided into k classes and the sampling data come out from a two stage stratified sampling. The main purpose of the work is to determine the estimators, as well as their asymptotic distribution, of the partial means of classes, each of them is defined as a non linear function of the other parameters. Particularly, we are interested in determining the linear approximation estimators and, under convergence theorems, the asymptotic distribution. Afterwards we define the estimator of the vector of the partial means of classes and its asymptotic convergence to multivariate normal distribution is determined. These results are useful to develop simultaneous inferential procedures.     

Regional Well-Being and its Inequality in the OECD Member Countries

This paper analyses the inequality between the regions of the Organization for Economic Co-operation and Development (OECD) member countries by using stochastic multi-objective acceptability analysis and the associated multivariate Gini index. By considering a large number of possible combinations of weights, the distribution of the potential rankings for each region is used to measure multidimensional inequality both within and between countries. Our results show that beyond the expected two clubs of rich and poor countries, a third group of countries emerges that belongs neither to the top nor to the bottom of the ranking, an outcome that can be attributed to the presence of significant economic differences among regions within those countries. Most of the inequality lies between countries, but regional well-being also significantly varies within the same countries and we find an inverse U-shape connection between regional well-being and its inequality within the OECD member countries.

     

The Use of Risk Assessment to Decide the Control Strategy for Bluetongue in Italian Ruminant Populations

The affiliation, assessment and management of risks is a traditional part of veterinary medicine. In the past, veterinary services involved in this type of activity usually assessed risks qualitatively. However, since the 1990s, quantitative methods have become increasingly important. The establishment of the World Trade Organization in 1994, and the promulgation of its Agreement on the Application of Sanitary and Phytosanitary Measures (the "SPS Agreement") led to an increased application of import risk analysis and to significant improvements in the methodology of risk analysis as applied to international trade policy for animals and animal products. However, there was very little development of risk analysis in veterinary fields other than international trade and management of health risks to consumers of animal products and little has been published on its use in the choice and definition of control or prophylaxis strategies for animal diseases. This article describes a quantitative risk assessment, which was undertaken in Italy to help choose an appropriate national response strategy following an incursion of bluetongue, an infectious disease of sheep and goats. The results obtained in this study support the use of risk analysis as a tool to assist in choosing an appropriate animal disease management strategy. The use of risk analysis in the evaluation of disease management strategies also offers advantages in international trade. It makes easier the comparison of different strategies applied in the various countries, and thus facilitates the assessment of equivalence of the guarantees provided by different strategies.     

Guilt in Marketing Research: An Elicitation–Consumption Perspective and Research Agenda

Guilt regulates many consumption processes and, consequently, marketers frequently use appeals based on guilt to influence consumers' behaviour. Owing to the multidisciplinary interest in this emotion, however, the literature is diverse and fragmented. The effectiveness of guilt appeals is contested, and some authors suggest that the use of this emotion in marketing might be unethical. Furthermore, research to date has not explored the potential relationships between the experience of guilt in consumption and the elicitation of this emotion through marketing appeals. This paper analyses existing research on guilt in marketing, developing four specific contributions based on the evidence reviewed. First, it shows under what circumstances feelings of guilt support consumer self‐regulation processes. Second, it outlines evidence‐based managerial recommendations on how to produce effective guilt appeals and avoid the potentially unethical consequences of marketing through this emotion. Third, it identifies a gap in existing theorizing and presents an elicitation–consumption perspective of guilt in marketing as a framework that complements current approaches to this research topic. Fourth, it develops an agenda for future research and suggests eleven research hypotheses for the advancement of this field. Through the analysis of research produced within different disciplinary perspectives, this study develops a necessary foundation for future work on the role of guilt in marketing processes.     

An Integrated Model of Cumulative Growth: Empirical Evidence for Nine OECD Countries, 1960-1990

ABSTRACT: This paper is an empirical analysis of the interaction between the dynamics of demand, productivity and employment in nine industrial countries: the United States, Canada, Japan, West Germany, France, Italy, the United Kingdom, the Netherlands and Belgium, 1960-1990. Its theoretical framework derives from the Kaldorian approach to cumulative growth in both its external and internal causation versions. The model we adopt is of an integrated kind, in which foreign demand is determined endogenously and domestic demand is divided into various component parts: exogenous for the public sector and endogenous for the private. More specifically, this is carried out by describing the way the dynamics of private consumption and private investments depend on economic variables located in the spheres of distribution and of technology, so that we can consider the operations of income compensation effects induced by technological change — via changes in income and its social distribution — as well as price compensation effects— the higher competitiveness of national products in foreign markets — mediated through the dynamics of exports.     

A New Relative Importance Index of Evaluation for Conjoint Analysis: Some Findings for CRM Assistant

Social Indicators Research - ELECTUS is an Italian multi-centre research project with the aim of reinforcing the relationship between the academic world and business. Through this project, it is...     

Single-cell antisense RNA amplification and microarray analysis as a tool for studying neurological degeneration and restoration

Neurodegenerative diseases typically affect subpopulations of neurons. Characterizing these vulnerable cells and identifying the factors that make them susceptible to damage while neighboring cells remain resistant are essential to the understanding of molecular pathogenesis that underlies neurodegenerative diseases. Classically, molecular analysis of the central nervous system involves the identification and isolation of an anatomic region of interest; next, the relevant tissue is pulverized, and the resulting homogenate is analyzed. Although this method provides useful data, its effectiveness diminishes when used in areas of high cellular diversity or in instances in which one cell type is lost as a consequence of selective cell death or quiescence. A technique that affords the ability to assess molecular events in a very precise anatomical site would provide a powerful tool for this research discipline. In this review, we discuss the amplification of messenger RNA from single neural cells and the subsequent use of the RNA to probe DNA microarrays in an effort to create cell-specific molecular profiles. Specifically, recent work in single-cell expression profiling in Alzheimer's and Huntington's diseases is discussed. We also review some new work with neural stem cells and their application to restorative neurobiology. Finally, we discuss the use of cell-specific molecular profiles to better understand the basics of neuronal cell biology.