On the estimation of the Lorenz curve under complex sampling designs

Statistical Methods & Applications - This paper focuses on the estimation of the concentration curve of a finite population, when data are collected according to a complex sampling design with...     

A unified approach to permutation testing for equivalence

Statistical Methods & Applications - The notion of testing for equivalence of two treatments is widely used in clinical trials, pharmaceutical experiments, bioequivalence and quality control....     

U.N.H.C.R. as a bulwark against violations of migrants’ rights. Dialogue with Stephane Jacquemet

Stephane Jacquemet, Regional Representative for Southern Europe of the Office of the United Nations High Commissioner for Refugees (U.N.H.C.R.) since April 2016, agreed to answer some questions regarding U.N.H.C.R.’s mandate and positions in relation to the so-called ‘European migration crisis’. Mr Jacquemet is a Swiss Lawyer who has been working with the U.N.H.C.R. for 24 years. In 1992 he was called as Head of Operations in Croatia, and during his career he served in Togo, Indonesia, Lebanon, Nepal, Burkina Faso, and Colombia. Between 1997 and 2002 Mr Jacquemet held a number of senior positions in the Division of International Protection at U.N.H.C.R. Headquarters in Geneva. This rare and invaluable combination of legal and practical expertise makes Mr Jacquemet a first-class interlocutor whom to ask some questions concerning, on the one hand, the E.U. policies towards migrants, and, on the other, U.N.H.C.R.'s strategies in relation to the promotion of refugees’ and statelessness persons’ rights.     

The Dimensions of Agricultural Diversification: A Spatial Analysis of Italian Municipalities

Diversification in agriculture could ensure the survival of farming by broadening the income base of farms and encouraging agricultural sustainability. The diversification of on-farm activities may depend on socioeconomic and environmental characteristics. Although multifunctionality is a hotly debated topic, few papers have focused on the farm characteristics that influence diversification and none have focused on the influence of the spatial pattern. This paper examines the relationship between farm characteristics and the adoption of a specific type of diversification. An econometric model is presented that uses a spatial autoregressive lag model at the municipal scale. The results demonstrate that the activation of each diversification dimension is influenced by both internal and external factors, encompassing farmers’ characteristics, the farm structure, and territorial features, including regional and spatial patterns. Deepening is mainly influenced by the farmer’s age, education, and the presence of small and labor-intensive farms. The key factors for broadening diversification are the presence of small farms and farms with mixed production (breeding and crop cultivation). Regrounding is most affected by the labor-intensive farms in the area and the farms with mixed production.     

A Permutation Solution to Test for Treatment Effects in Alternation Design Single-Case Experiments

Research involving a clinical intervention is normally aimed at testing the treatment effects on a dependent variable, which is assumed to be a relevant indicator of health or quality-of-life status. In much clinical research large-n trials are in fact impractical because the availability of individuals within well-defined categories is limited in this application field. This makes it more and more important to concentrate on single-case experiments. The goal with these is to investigate the presence of a difference in the effect of the treatments considered in the study. In this setting, valid inference generally cannot be made using the parametric statistical procedures that are typically used for the analysis of clinical trials and other large-n designs. Hence, nonparametric tools can be a valid alternative to analyze this kind of data. We propose a permutation solution to assess treatment effects in single-case experiments within alternation designs. An extension to the case of more than two treatments is also presented. A simulation study shows that the approach is both reliable under the null hypothesis and powerful under the alternative, and that it improves the performance of a considered competitor. In the end, we present the results of a real case application.     

Extensions of Permutation Solutions to Test for Treatment Effects in Replicated Single-Case Alternation Experiments with Multivariate Response

Single-case experiments are frequently used to do research involving a clinical intervention, since large-n trials are often impractical in clinical research. In order to investigate a possible difference in the effect of the treatments considered in the study, nonparametric instruments are valid tools; in particular, permutation solutions work well when we wish to assess differences in treatment effects. We present an extension of a permutation solution to the multivariate response case and to the case of replicated single-case experiments. A simulation study shows that the approach is both reliable under the null hypothesis and powerful under the alternative. At the end, we present the results of an application to two real experiments.     

A Discussion on Nonlinear Models for Price Decisions in Rating-Based Product Preference Models

The purpose of this article is to discuss the application of nonlinear models to price decisions in the framework of rating-based product preference models. As revealed by a comparative simulation study, when a nonlinear model is the true model, the traditional linear model fails to properly describe the true pattern. It appears to be unsatisfactory in comparison with nonlinear models, such as logistic and natural spline, which offer some advantages, the most important being the ability to take into account more than just linear and/or monotonic effects. Consequently, when we model the product preference with a nonlinear model, we are potentially able to detect its ‘best’ price level, i.e., the price at which consumer preference towards a given attribute is at its maximum. From an application point of view, this approach is very flexible in price decisions and may produce original managerial suggestions which might not be revealed by traditional methods.     

Combination-Based Permutation Tests: Equipower Property and Power Behavior in Presence of Correlation

Multivariate combination-based permutation tests have been widely used in many complex problems. In this paper we focus on the equipower property, derived directly from the finite-sample consistency property, and we analyze the impact of the dependency structure on the combined tests. At first, we consider the finite-sample consistency property which assumes that sample sizes are fixed (and possibly small) and considers on each subject a large number of informative variables. Moreover, since permutation test statistics do not require to be standardized, we need not assume that data are homoscedastic in the alternative. The equipower property is then derived from these two notions: consider the unconditional permutation power of a test statistic T for fixed sample sizes, with V ? 2 independent and identically distributed variables and fixed effect δ, calculated in two ways: (i) by considering two V-dimensional samples sized m₁ and m₂, respectively; (ii) by considering two unidimensional samples sized n₁ = Vm₁ and n₂ = Vm₂, respectively. Since the unconditional power essentially depends on the non centrality induced by T, and two ways are provided with exactly the same likelihood and the same non centrality, we show that they are provided with the same power function, at least approximately. As regards both investigating the equipower property and the power behavior in presence of correlation we performed an extensive simulation study.     

WHAT DETERMINES ENTREPRENEURIAL CLUSTERS?

We contrast two potential explanations of the substantial differences in entrepreneurial activity observed across geographical areas: entry costs and external effects. We extend the Lucas model of entrepreneurship to allow for heterogeneous entry costs and for externalities that shift the distribution of entrepreneurial talents. We show that these assumptions have opposite predictions on the relation between entrepreneurial activity and firm‐level TFP: with different entry costs, in areas with more entrepreneurs firms' average productivity should be lower; with heterogeneous external effects it should be higher. We test these implications on a sample of Italian firms and unambiguously reject the entry costs explanation in favor of the externalities explanation. We also investigate the sources of external effects, finding robust evidence that learning externalities are an important determinant of cross‐sectional differences in entrepreneurial activity.     

Visualizing main effects and interaction in multiple non-symmetric correspondence analysis

Non-symmetric correspondence analysis (NSCA) is a useful technique for analysing a two-way contingency table. Frequently, the predictor variables are more than one; in this paper, we consider two categorical variables as predictor variables and one response variable. Interaction represents the joint effects of predictor variables on the response variable. When interaction is present, the interpretation of the main effects is incomplete or misleading. To separate the main effects and the interaction term, we introduce a method that, starting from the coordinates of multiple NSCA and using a two-way analysis of variance without interaction, allows a better interpretation of the impact of the predictor variable on the response variable. The proposed method has been applied on a well-known three-way contingency table proposed by Bockenholt and Bockenholt in which they cross-classify subjects by person's attitude towards abortion, number of years of education and religion. We analyse the case where the variables education and religion influence a person's attitude towards abortion.