On unit free assessment of the extent of multilateral distributional variation

Summary Multilateral comparison of outcomes drawn from multiple groups pervade the social sciences and measurement of their variability, usually involving functions of respective group location and scale parameters, is of intrinsic interest. However, such approaches frequently mask more fundamental differences that more comprehensive examination of relative group distributional structures reveal. Indeed, in categorical data contexts, location- and scale-based techniques are no longer feasible without artificial and questionable cardinalisation of categories. Here, Gini’s transvariation measure is extended and employed in providing quantitative and visual multilateral comparison tools in discrete, continuous, categorical, univariate, or multivariate settings which are particularly useful in paradigms where cardinal measure is absent. Two applications, one analysing Eurozone cohesion in terms of the convergence or divergence of constituent nations income distributions, the other, drawn from a study of ageing, health, and income inequality in China, exemplify their use in a continuous and categorical data environment.

How to do (or not to do) … a health financing incidence analysis

Financing incidence analysis (FIA) assesses how the burden of health financing is distributed in relation to household ability to pay (ATP). In a progressive financing system, poorer households contribute a smaller proportion of their ATP to finance health services compared to richer households. A system is regressive when the poor contribute proportionately more. Equitable health financing is often associated with progressivity. To conduct a comprehensive FIA, detailed household survey data containing reliable information on both a cardinal measure of household ATP and variables for extracting contributions to health services via taxes, health insurance and out-of-pocket (OOP) payments are required. Further, data on health financing mix are needed to assess overall FIA. Two major approaches to conducting FIA described in this article include the structural progressivity approach that assesses how the share of ATP (e.g. income) spent on health services varies by quantiles, and the effective progressivity approach that uses indices of progressivity such as the Kakwani index. This article provides some detailed practical steps for analysts to conduct FIA. This includes the data requirements, data sources, how to extract or estimate health payments from survey data and the methods for assessing FIA. It also discusses data deficiencies that are common in many low- and middle-income countries (LMICs). The results of FIA are useful in designing policies to achieve an equitable health system.

NEW ADVANCES OF THE COMPATIBILITY INDEX “G” IN WEIGHTED ENVIRONMENTS

This article addresses the problem of measuring closeness in weighted environments (decision-making environments). This article is relevant because of the importance of having a dependable cardinal measure of distance in weighted environments. A weighted environment is a non-isotropic structure where the different directions (axes) may have different importance (weight) hence, privileged directions exist. In this kind of a structure, it would be very important to have a cardinal reliable index that is able to show how close or compatible the set of measures of one individual is with respect to the group or to any other, or how close one pattern of behavior is to another. A few common examples of the application of this are the interaction between actors in a decision making process (system values interaction), matching profiles, pattern recognition, and any situation where a process of measurement with qualitative variables is involved.

Constructing a Cardinal Measure of Democratic Development in a Transition Polity: The Nigerian Example

In the last decade, the political institutions and practices under which economic decisions are made have received increasing attention in the analysis of the responsibility for economic underperformance. This attention has in turn led to a questioning of the issues of conceptualization and measurement of the variables involved. While economic variables are easily conceptualized and measured, political institutional factors present some difficulty. Although the aim of a democratic system is to assure the rights and freedoms for the citizens of a polity, for those polities in transition, the processes that drive societies towards or away from higher rights and freedoms for their citizens are more important. This paper attempts to cover the following topics: first, to construct measurable variables of democratization that can be used to determine the level of democratic development in a transition polity; and second, to apply these variables to determine the level and patterns of democratization in Nigeria. Section two highlights significant past research which has measured the levels of democracy across different countries. In section three Nigeriaxi' s political history is summarized to show a polity in continuing political transition. Section four identifies relevant dimensions of democratization in a transition polity. Section five applies the dimensions to derive indices to measure the level of democratization in Nigeria. In section six the pattern of the democratization process in Nigeria is established. Section seven justifies the measures for transition polities and suggests the use to which they may be put.